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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | 15 days ago
. Nous étudierons les relations entre les caractéristiques intrinsèques et extrinsèques de la MW, à l'aide d'une approche multimodale (imagerie spatiale/hyperion, immunofluorescence multiplex, séquençage
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(transformative) effects on the reader. A literary analysis may also be conducted in tandem with an analysis of the lay-out/spatial arrangement of these texts within the handwritten codices: how does lay-out affect
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working knowledge of GIS platforms (e.g., ArcGIS, QGIS) and spatial data analysis techniques. Training or demonstrated experience in remote sensing, spatial data collection, and thematic mapping
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or fragments). Practical experience of complex tissue analysis using multistaining techniques and image analysis. Practical experience of analysis of spatial proteomics and/or transcriptomics data. Experience
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consequences for essential ecosystem processes. In the framework of the Biodiversity Exploratories (https://www.biodiversity-exploratories.de/en/ ), funded by the German Research Foundation (DFG), the project
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methods for spatial transcriptomics, advanced microscopy, volumetric imaging, neuronal activity mapping, and multimodal data analysis, with an initial focus on neuroscience. To build this interdisciplinary
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open-source software packages and set up computational pipelines. As a bio-informatics research lab, we publish software packages in Python and R for specific, cutting-edge analysis of large-scale
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Basic and Applied Spatial Analysis Lab (BASAL). The BASAL is located within the Department of Natural Resources and the Environment at the University of New Hampshire. This researcher will work directly
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multidisciplinary experience in combining integrative computational immunology – data-driven, state-of-the-art single cell resolution and spatial methods, machine learning and kinetic modeling – with integrative
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in applied economic analysis (e.g., causal inference, econometrics, spatial equilibrium modeling). • Experience working with large-scale datasets and interdisciplinary research. • Demonstrated research